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Reference for ultralytics/models/yolo/pose/predict.py

Note

This file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/yolo/pose/predict.py. If you spot a problem please help fix it by contributing a Pull Request 🛠️. Thank you 🙏!


ultralytics.models.yolo.pose.predict.PosePredictor

PosePredictor(cfg=DEFAULT_CFG, overrides=None, _callbacks=None)

Bases: DetectionPredictor

A class extending the DetectionPredictor class for prediction based on a pose model.

Example
from ultralytics.utils import ASSETS
from ultralytics.models.yolo.pose import PosePredictor

args = dict(model="yolo11n-pose.pt", source=ASSETS)
predictor = PosePredictor(overrides=args)
predictor.predict_cli()
Source code in ultralytics/models/yolo/pose/predict.py
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
    """Initializes PosePredictor, sets task to 'pose' and logs a warning for using 'mps' as device."""
    super().__init__(cfg, overrides, _callbacks)
    self.args.task = "pose"
    if isinstance(self.args.device, str) and self.args.device.lower() == "mps":
        LOGGER.warning(
            "WARNING ⚠️ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
            "See https://github.com/ultralytics/ultralytics/issues/4031."
        )

construct_result

construct_result(pred, img, orig_img, img_path)

Constructs the result object from the prediction.

Parameters:

Name Type Description Default
pred Tensor

The predicted bounding boxes, scores, and keypoints.

required
img Tensor

The image after preprocessing.

required
orig_img ndarray

The original image before preprocessing.

required
img_path str

The path to the original image.

required

Returns:

Type Description
Results

The result object containing the original image, image path, class names, bounding boxes, and keypoints.

Source code in ultralytics/models/yolo/pose/predict.py
def construct_result(self, pred, img, orig_img, img_path):
    """
    Constructs the result object from the prediction.

    Args:
        pred (torch.Tensor): The predicted bounding boxes, scores, and keypoints.
        img (torch.Tensor): The image after preprocessing.
        orig_img (np.ndarray): The original image before preprocessing.
        img_path (str): The path to the original image.

    Returns:
        (Results): The result object containing the original image, image path, class names, bounding boxes, and keypoints.
    """
    result = super().construct_result(pred, img, orig_img, img_path)
    pred_kpts = pred[:, 6:].view(len(pred), *self.model.kpt_shape) if len(pred) else pred[:, 6:]
    pred_kpts = ops.scale_coords(img.shape[2:], pred_kpts, orig_img.shape)
    result.update(keypoints=pred_kpts)
    return result



📅 Created 1 year ago ✏️ Updated 4 months ago